https://github.com/davmixcool/php-sentiment-analyzer
PHP Sentiment Analyzer is a lexicon and rule-based sentiment analysis tool that is used to understand sentiments in a sentence using VADER (Valence Aware Dictionary and sentiment Reasoner).
https://github.com/davmixcool/php-sentiment-analyzer
Last synced: 10 months ago
JSON representation
PHP Sentiment Analyzer is a lexicon and rule-based sentiment analysis tool that is used to understand sentiments in a sentence using VADER (Valence Aware Dictionary and sentiment Reasoner).
- Host: GitHub
- URL: https://github.com/davmixcool/php-sentiment-analyzer
- Owner: davmixcool
- License: mit
- Created: 2018-08-29T13:07:41.000Z (over 7 years ago)
- Default Branch: master
- Last Pushed: 2022-10-15T06:37:10.000Z (over 3 years ago)
- Last Synced: 2025-03-29T07:05:41.819Z (10 months ago)
- Language: PHP
- Homepage:
- Size: 161 KB
- Stars: 139
- Watchers: 5
- Forks: 37
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Funding: .github/FUNDING.yml
Awesome Lists containing this project
- awesome-php-ml - davmixcool/php-sentiment-analyzer
README
# PHP Sentiment Analyzer
PHP Sentiment Analyzer is a lexicon and rule-based sentiment analysis tool that is used to understand sentiments in a sentence using VADER \(Valence Aware Dictionary and sentiment Reasoner\).
[](https://github.com/davmixcool/php-sentiment-analyzer/blob/master/LICENSE) [](https://github.com/davmixcool/php-sentiment-analyzer/issues) [](https://poser.pugx.org/davmixcool/php-sentiment-analyzer/v/stable.svg) [](https://poser.pugx.org/davmixcool/php-sentiment-analyzer/d/total.svg) [](https://twitter.com/intent/tweet?text=Wow:&url=https%3A%2F%2Fgithub.com%2Fdavmixcool%2Fphp-sentiment-analyzer)
## Features
* Text
* Emoticon
* Emoji
## Requirements
* PHP 5.5 and above
## Steps:
* [Install](./#install)
* [Usage](./#usage)
* [Stargazers](./#stargazers)
* [Forkers](./#forkers)
* [License](./#license)
* [Reference](./#reference)
### Install
**Composer**
Run the following to include this via Composer
```text
composer require davmixcool/php-sentiment-analyzer
```
### Simple Usage
```php
Use Sentiment\Analyzer;
$analyzer = new Analyzer();
$output_text = $analyzer->getSentiment("David is smart, handsome, and funny.");
$output_emoji = $analyzer->getSentiment("😁");
$output_text_with_emoji = $analyzer->getSentiment("Aproko doctor made me 🤣.");
print_r($output_text);
print_r($output_emoji);
print_r($output_text_with_emoji);
```
### Simple Outputs
```text
David is smart, handsome, and funny. ---------------- ['neg'=> 0.0, 'neu'=> 0.337, 'pos'=> 0.663, 'compound'=> 0.7096]
😁 ------------------- ['neg' => 0, 'neu' => 0.5, 'pos' => 0.5, 'compound' => 0.4588]
Aproko doctor made me 🤣 ------------- ['neg' => 0, 'neu' => 0.714, 'pos' => 0.286, 'compound' => 0.4939]
```
### Advanced Usage
You can now dynamically update the VADER \(Valence\) lexicon on the fly for words that are not in the dictionary. See the Example below:
```php
Use Sentiment\Analyzer;
$sentiment = new Sentiment\Analyzer();
$strings = [
'Weather today is rubbish',
'This cake looks amazing',
'His skills are mediocre',
'He is very talented',
'She is seemingly very agressive',
'Marie was enthusiastic about the upcoming trip. Her brother was also passionate about her leaving - he would finally have the house for himself.',
'To be or not to be?',
];
//new words not in the dictionary
$newWords = [
'rubbish'=> '-1.5',
'mediocre' => '-1.0',
'agressive' => '-0.5'
];
//Dynamically update the dictionary with the new words
$sentiment->updateLexicon($newWords);
//Print results
foreach ($strings as $string) {
// calculations:
$scores = $sentiment->getSentiment($string);
// output:
echo "String: $string\n";
print_r(json_encode($scores));
echo "
";
}
```
### Advanced Outputs
```text
Weather today is rubbish ------------- {"neg":0.455,"neu":0.545,"pos":0,"compound":-0.3612}
This cake looks amazing ------------- {"neg":0,"neu":0.441,"pos":0.559,"compound":0.5859}
His skills are mediocre ------------- {"neg":0.4,"neu":0.6,"pos":0,"compound":-0.25}
He is very talented ------------- {"neg":0,"neu":0.457,"pos":0.543,"compound":0.552}
She is seemingly very agressive ------------- {"neg":0.338,"neu":0.662,"pos":0,"compound":-0.2598}
Marie was enthusiastic about the upcoming trip. Her brother was also passionate about her leaving - he would finally have the house for himself. ------------- {"neg":0,"neu":0.761,"pos":0.239,"compound":0.765}
String: To be or not to be? ------------- {"neg":0,"neu":1,"pos":0,"compound":0}
```
### Stargazers
[](https://github.com/davmixcool/php-sentiment-analyzer/stargazers)
### Forkers
[](https://github.com/davmixcool/php-sentiment-analyzer/network/members)
### License
This package is licensed under the [MIT license](https://github.com/davmixcool/php-sentiment-analyzer/blob/master/LICENSE).
### Reference
Hutto, C.J. & Gilbert, E.E. \(2014\). VADER: A Parsimonious Rule-based Model for Sentiment Analysis of Social Media Text. Eighth International Conference on Weblogs and Social Media \(ICWSM-14\). Ann Arbor, MI, June 2014.